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Pré-Publication, Document De Travail Année : 2017

Estimating long memory in panel random-coefficient AR(1) data

Résumé

It is well-known that random-coefficient AR(1) process can have long memory depending on the index β of the tail distribution function of the random coefficient, if it is a regularly varying function at unity. We discuss estimation of β from panel data comprising N random-coefficient AR(1) series, each of length T. The estimator of β is constructed as a version of the tail index estimator of Goldie and Smith (1987) applied to sample lag 1 autocorrelations of individual time series. Its asymptotic normality is derived under certain conditions on N, T and some parameters of our statistical model. Based on this result, we construct a statistical procedure to test if the panel random-coefficient AR(1) data exhibit long memory. A simulation study illustrates finite-sample performance of the introduced estimator and testing procedure.
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Dates et versions

hal-01622201 , version 1 (25-10-2017)
hal-01622201 , version 2 (29-10-2018)
hal-01622201 , version 3 (13-09-2019)

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Remigijus Leipus, Anne Philippe, Vytaute Pilipauskaite, Donatas Surgailis. Estimating long memory in panel random-coefficient AR(1) data. 2017. ⟨hal-01622201v3⟩
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